Description:

Design, develop, and deploy end-to-end data pipelines on AWS cloud infrastructure using services like Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.
Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics and reporting needs.
Build and maintain orchestration workflows with Apache Airflow to automate data pipeline execution, scheduling, and monitoring.
Collaborate with data scientists, analysts, and business stakeholders to comprehend data requirements and provide scalable data solutions.
Optimize data pipelines for performance, reliability, and cost-effectiveness, utilizing AWS best practices and cloud-native technologies.

Requirements:

8+ years of experience constructing and deploying large-scale data processing pipelines in a production setting.
Hands-on expertise in designing and building data pipelines on AWS cloud infrastructure.
Proficiency in AWS services like Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.
Experience with Databricks and Apache Spark for data processing and analytics.
Familiarity with Apache Airflow for orchestrating and scheduling data pipelines.
Understanding of data modeling, database design principles, and SQL.
Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
Strong problem-solving skills and attention to detail.

This role provides an excellent opportunity for significant career growth in a fast-growing and challenging entrepreneurial environment with a high level of individual responsibility.